Integrated Modeling of Adaptive Neuronal Regulation

描述（由申请人提供）： 内环境稳态的丧失是指机体内环境在功能容许范围内的动态维持，被认为是疾病发生和发展的中心环节。这项建议的中心目标是发展新的见解，稳态的机制，因为它涉及脑干孤束核（NTS）和神经调节剂血管紧张素II（AngII）在高血压中的作用。NTS是中枢神经元协调稳态的关键整合结构，而AngII是哺乳动物生物学中最具多效性活性的分子之一，因此在生物医学上是重要的。NTS神经元对Ang II的反应，通过AT 1 R起作用，涉及通过（1）通过细胞内信号调节的膜离子通道和（2）在互连网络中起作用的多个基因的表达动力学的相互作用影响神经元电生理学的过程。这两者都有助于适应性NTS反应，该反应有助于疾病中改变的稳态功能的发展和维持。目标是从分子水平的相互作用网络到电生理信号产生的桥梁。这里讨论的问题是大脑功能和生理学的基础;特别是与调节对各种刺激的反应有关。为此，我们专注于AT 1 R诱导的神经调制在两个不同的时间水平，在两个特定的目的。目的1：基于实验数据，建立一个膜离子通道电流快速瞬态调制的数学模型，重点研究AT 1受体-信号-电生理。这将支持信号通路和生物物理过程的详细相互作用的模拟研究的短期到中期的时间框架适应性电生理活动模式。将使用通路抑制剂对模型预测进行实验验证，并将结果反复用于进一步的模型优化。目标2的重点是开发和实验验证NTS中AT 1 R激活下游调控网络的数学模型。为此，我们将遵循我们以前开发的结构化方法，将联合收割机微阵列基因表达数据和关键转录因子的启动子占用率结合起来。将使用基于染色质免疫沉淀（ChIP）的方法对网络假设进行实验验证，并将结果迭代用于进一步完善调控网络模型。这些目标的成功完成将提供参与NTS对AT 1 R激活的适应性反应的分子机制的第一个系统水平分析，提供对稳态机制的见解。公共卫生相关性：体内平衡的丧失，定义为在功能可耐受的限度内动态维持内部环境，被认为是疾病开始和进展的核心。本项目基于这样的假设，即这些过程来自复杂和动态的神经元过程，这些过程涉及多个信号分子和基因，随着时间的推移，在一个分层和相互连接的网络中发挥作用。我们的目标是将联合收割机计算模型与实验测量相结合，以发展和验证潜在的分子机制的假设。

DESCRIPTION (provided by applicant): Abstract Loss of homeostasis, defined as the dynamic maintenance of the internal environment within functionally tolerable limits, is understood as central to the initiation and progression of disease. The central objective of this proposal is to develop new insights into the mechanisms of homeostasis as it involves the brainstem nucleus tractus solitarius (NTS) and the role of the neuromodulator Angiotensin II (AngII) in hypertension. The NTS is a key integrative structure in the central neuronal orchestration of homeostasis, while AngII is one of the most pleiotropically active and therefore biomedically important molecules in mammalian biology. The NTS neuronal response to Ang II, acting through AT1R, involves processes that affect neuronal electrophysiology via the interplay of (1) membrane ion channels modulated via intracellular signaling, and (2) expression dynamics of multiple genes functioning in an interconnected network. Both of these contribute to the adaptive NTS response that contributes to the development and maintenance of changed homeostatic function in disease. The goal is for bridging from molecular level interaction networks to electrophysiological signal generation. The questions addressed here are fundamental for brain functioning and physiology; in particular, in connection to regulation of the response to various stimuli. To this end, we focus on the AT1R induced neuromodulation at two different temporal levels, in two Specific Aims. Aim 1, with focus on the AT1 receptor- to-signaling-to-electrophysiology, will develop a mathematical model of the rapid and transient modulation of membrane ion channel currents based on experimental data. This will support simulation study of the detailed interaction of signaling pathways and biophysical processes underlying short-to-intermediate timeframe adaptive electrophysiological activity patterns. Model predictions will be experimentally validated using pathway inhibitors and the results iteratively utilized in further model refinement. The focus of Aim 2 is to develop and experimentally validate a mathematical model of the regulatory network downstream of AT1R activation in NTS. To this end, we will follow a structured approach that we have previously developed to combine microarray gene expression data and promoter occupancy of key transcription factors. The network hypotheses will be experimentally validated using Chromatin ImmunoPrecipitation (ChIP)-based methods and the results will be used iteratively in further refinement of the regulatory network model. Successful completion of these Aims will provide the first systems level analysis of molecular mechanisms involved in the NTS adaptive response to AT1R activation, providing insights into the mechanisms of homeostasis. PUBLIC HEALTH RELEVANCE: Project Narrative Loss of homeostasis, defined as the dynamic maintenance of the internal environment within functionally tolerable limits, is understood as central to the initiation and progression of disease. The present project is based on the hypothesis that these processes arise from complex and dynamic neuronal processes that involve multiple signaling molecules and genes functioning over time in a hierarchical and interconnected network. We aim to combine computational models with experimental measurements in order to develop and validate hypotheses of the underlying molecular mechanisms.